test for the newly added optimizations

theano/tensor/tests/test_opt.py

@@ -1582,6 +1582,78 @@ class test_local_subtensor_merge(unittest.TestCase):
                                     f(x_val, b1,e1,s1,b2,e2,s2)
 
 
+def test_setsubtensor_allocs0():
+    x = tensor.matrix()
+    y = tensor.matrix()
+    x0 = tensor.zeros_like(x)
+    y0 = tensor.zeros_like(y)
+    z  = tensor.set_subtensor(x0[:4], y0)
+    f = theano.function([x,y], z)
+    assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
+                       f.maker.env.toposort() ])
+
+def test_setsubtensor_allocs1():
+    y = tensor.matrix()
+    x0 = tensor.constant(numpy.asarray(numpy.zeros_like((4,4)), dtype=config.floatX))
+    y0 = tensor.zeros_like(y)
+    z  = tensor.set_subtensor(x0[:4], y0)
+    f = theano.function([y], z)
+    assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
+                       f.maker.env.toposort() ])
+
+def test_setsubtensor_allocs2():
+    x = tensor.matrix()
+    y0 = tensor.constant(numpy.asarray(numpy.zeros_like((4,4)), dtype=config.floatX))
+    x0 = tensor.zeros_like(y)
+    z  = tensor.set_subtensor(x0[:4], y0)
+    f = theano.function([x], z)
+    assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
+                       f.maker.env.toposort() ])
+
+def test_incsubtensor_allocs0():
+    x = tensor.matrix()
+    y = tensor.matrix()
+    y0 = tensor.zeros_like(y)
+    z  = tensor.inc_subtensor(x[:4], y0)
+    f = theano.function([x,y], z)
+    assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
+                       f.maker.env.toposort() ])
+
+def test_incsubtensor_allocs1():
+    x = tensor.matrix()
+    y0 = tensor.constant(numpy.asarray(numpy.zeros_like((4,4)), dtype=config.floatX))
+    z  = tensor.inc_subtensor(x[:4], y0)
+    f = theano.function([x], z)
+    assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
+                       f.maker.env.toposort() ])
+
+
+def test_dot_allocs_0():
+    v1 = tensor.vector('v1')
+    v2 = tensor.vector('v2')
+    m1 = tensor.matrix('m1')
+    m2 = tensor.matrix('m2')
+    vv = numpy.asarray([0,1,2], dtype = theano.config.floatX)
+    vm = numpy.asarray([[1,2,3],[4,5,6],[7,8,9]],
+                       dtype=theano.config.floatX)
+    for _e1 in [(v1,vv),(m1,vm)]:
+        for _e2 in [(v2,vv),(m2,vm)]:
+            for p in [0,1]:
+                if p == 0:
+                    e1 = tensor.zeros_like(_e1[0])
+                    e2 = _e2[0]
+                else:
+                    e1 = _e1[0]
+                    e2 = tensor.zeros_like(_e2[0])
+                o = tensor.dot(e1,e2)
+                f = theano.function([_e1[0],_e2[0]], o)
+                f(_e1[1], _e2[1])
+                assert numpy.all([ not isinstance(x.op, tensor.Dot) for x in
+                                  f.maker.env.toposort() ])
+
+
+
+
 def test_local_fill_useless():
     m = theano.config.mode
     if m == 'FAST_COMPILE':